Optimal Recourse Strategy for Battery Swapping Stations Considering Electric Vehicle Uncertainty
| Autor: | William Infante, Jin Ma, Xiaoqing Han, Ariel Liebman |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Battery (electricity)
050210 logistics & transportation business.product_category Operations research Computer science business.industry Mechanical Engineering 05 social sciences Investment (macroeconomics) Computer Science Applications 0502 economics and business Automotive Engineering Electric vehicle Sensitivity (control systems) Electricity business Cluster analysis |
| Zdroj: | IEEE Transactions on Intelligent Transportation Systems. 21:1369-1379 |
| ISSN: | 1558-0016 1524-9050 |
| DOI: | 10.1109/tits.2019.2905898 |
| Popis: | Battery swapping stations (BSSs) present an alternative way of charging electric vehicles (EVs) that can lead toward a sustainable EV ecosystem. Although research focusing on the BSS strategies has been ongoing, the results are fragmented. Currently, an integrated way of considering stochastic EV station visits through planning and operations has not been fully investigated. To create comprehensive and resilient battery swapping stations, a two-stage optimization with recourse is proposed. In the planning stage, the investment for battery purchases is recommended even before the EV station visit uncertainties are made known. In the operation stage, the battery allocation decisions, such as charging, discharging, and swapping are then coordinated. To apply the recourse strategy in creating representative scenarios, the EV station visit distribution techniques are also proposed using a modified K-means clustering method. Aside from the sensitivity analysis made with swapping prices and charging intervals, the strategy comparisons with conventional strategies have also demonstrated the practicality of the BSS coordination to future electricity and transportation networks. |
| Databáze: | OpenAIRE |
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